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deepgram-js-audio-intelligence

deepgram-js-audio-intelligence

github.com/deepgramData & databases27759 installsUpdated today
Repository

About deepgram-js-audio-intelligence

A JavaScript/TypeScript SDK skill for applying Deepgram Audio Intelligence features to audio transcription. It covers REST analytics and the smaller set available through WebSockets.

Key features

  1. 01Summaries, topics, and intents
  2. 02Sentiment and language detection
  3. 03Speaker diarization and redaction
  4. 04Entity detection with transcription

Use cases

  1. 01Analyze audio alongside its transcript
  2. 02Identify speakers in recorded audio
  3. 03Redact sensitive data from transcripts

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/deepgram/deepgram-js-sdk --skill deepgram-js-audio-intelligence

After installing, type/deepgram-js-audio-intelligencein Claude Code to confirm it loaded.

Details

From the project README

Using Deepgram Audio Intelligence (JavaScript / TypeScript SDK)

Analytics overlays applied to /v1/listen: summaries, topics, intents, sentiment, language detection, diarization, redaction, entities. Same client surface as STT; turn features on with parameters.

When to use this product

  • You have audio and want analytics returned alongside the transcript.
  • REST is the primary path; the WebSocket path supports only a subset of intelligence features.

Use a different skill when:

  • You just want transcript output → deepgram-js-speech-to-text.
  • You already have text and want analytics on that text → deepgram-js-text-intelligence.
  • You need Flux turn-taking → deepgram-js-conversational-stt.
  • You need a full interactive voice agent → deepgram-js-voice-agent.

Feature availability: REST vs WSS

FeatureRESTWSS
diarizeyesyes
redactyesyes
detect_entitiesyesyes
punctuate, smart_formatyesyes
summarizeyesno in current WSS connect args
topicsyesno
intentsyesno
sentimentyesno
detect_languageyesno

Authentication

require("dotenv").config();

const { DeepgramClient } = require("@deepgram/sdk");

const deepgramClient = new DeepgramClient({
  apiKey: process.env.DEEPGRAM_API_KEY,
});

Quick start — REST with analytics

From examples/22-transcription-advanced-options.ts:

const data = await deepgramClient.listen.v1.media.transcribeUrl({
  url: "https://dpgr.am/spacewalk.wav",
  model: "nova-3",
  language: "en",
  punctuate: true,
  paragraphs: true,
  utterances: true,
  smart_format: true,
  sentiment: true,
  topics: true,
  custom_topic: "custom_topic",
  custom_topic_mode: "extended",
  intents: true,
  custom_intent: "custom_intent",
  custom_intent_mode: "extended",
  detect_entities: true,
  detect_language: true,
  diarize: true,
  keyterm: ["keyword1", "keyword2"],
  redact: ["pci", "ssn"],
});

Quick start — WSS subset

Start from examples/07-transcription-live-websocket.ts and keep the same socket flow, but only use WSS-supported intelligence flags such as diarize, redact, and detect_entities in the connection args.

const deepgramConnection = await deepgramClient.listen.v1.createConnection({
  model: "nova-3",
  diarize: true,
  redact: "pci",
  detect_entities: true,
});

Key parameters / API surface

  • Analytics flags: summarize, topics, intents, sentiment, detect_language, detect_entities, diarize, redact, custom_topic, custom_topic_mode, custom_intent, custom_intent_mode.
  • Standard STT flags still apply: model, language, encoding, sample_rate, punctuate, smart_format, utterances, paragraphs, multichannel.
  • Nova-3-specific biasing in repo examples uses keyterm, not keywords.

API reference (layered)

  1. In-repo reference: reference.md → Listen V1 Media; WSS subset behavior lives in src/CustomClient.ts and src/api/resources/listen/resources/v1/client/{Client,Socket}.ts.
  2. Canonical OpenAPI (REST): https://developers.deepgram.com/openapi.yaml
  3. Canonical AsyncAPI (WSS): https://developers.deepgram.com/asyncapi.yaml
  4. Context7: library ID /llmstxt/developers_deepgram_llms_txt
  5. Product docs:

Gotchas

  1. summarize on /v1/listen is versioned, not plain boolean. The generated REST surface and examples point at "v2".
  2. Most intelligence flags are REST-only. Current WSS connect args do not expose topics, intents, sentiment, summarize, or detect_language.
  3. redact typing is looser in practice than in the generated alias. Examples pass arrays like ["pci", "ssn"], even though ListenV1Redact itself is just a string alias.
  4. Use keyterm for Nova-3 biasing. examples/22-transcription-advanced-options.ts explicitly notes keywords are not supported for Nova-3.
  5. Model/feature support is product-side. nova-3 is the safest choice when mixing many overlays.
  6. Diarization quality depends on audio quality and duration. Short or noisy clips churn speakers.

Example files in this repo

  • examples/22-transcription-advanced-options.ts
  • examples/04-transcription-prerecorded-url.ts
  • examples/05-transcription-prerecorded-file.ts
  • examples/07-transcription-live-websocket.ts

Central product skills

For cross-language Deepgram product knowledge — the consolidated API reference, documentation finder, focused runnable recipes, third-party integration examples, and MCP setup — install the central skills:

npx skills add deepgram/skills

This SDK ships language-idiomatic code skills; deepgram/skills ships cross-language product knowledge (see api, docs, recipes, examples, starters, setup-mcp).

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